loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Ales Jelinek and Ludek Zalud

Affiliation: Brno University of Technology, Czech Republic

ISBN: 978-989-758-198-4

Keyword(s): Vectorization, Point Cloud, Linear Regression, Least Squares Fitting, Mobile Robotics.

Related Ontology Subjects/Areas/Topics: Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Optimization Algorithms ; Optimization Problems in Signal Processing ; Robotics and Automation ; Signal Processing, Sensors, Systems Modeling and Control ; Vision, Recognition and Reconstruction

Abstract: Vectorization is a widely used technique in many areas, mainly in robotics and image processing. Applications in these domains frequently require both speed (for real-time operation) and accuracy (for maximal information gain). This paper proposes an optimization for the high speed vectorization methods, which leads to nearly optimal results. The FTLS algorithm uses the total least squares method for fitting the lines into the point cloud and the presented augmentation for the refinement of the results, is based on a modified NelderMead method. As shown on several experiments, this approach leads to better utilization of the information contained in the point cloud. As a result, the quality of approximation grows steadily with the number of points being vectorized, which was not achieved before. Performance costs are still comparable to the original algorithm, so the real-time operation is not endangered.

PDF ImageFull Text

Download
Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 54.92.148.165

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Jelinek, A. and Zalud, L. (2016). Augmented Postprocessing of the FTLS Vectorization Algorithm - Approaching to the Globally Optimal Vectorization of the Sorted Point Clouds.In Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-758-198-4, pages 216-223. DOI: 10.5220/0005962902160223

@conference{icinco16,
author={Ales Jelinek. and Ludek Zalud.},
title={Augmented Postprocessing of the FTLS Vectorization Algorithm - Approaching to the Globally Optimal Vectorization of the Sorted Point Clouds},
booktitle={Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2016},
pages={216-223},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005962902160223},
isbn={978-989-758-198-4},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - Augmented Postprocessing of the FTLS Vectorization Algorithm - Approaching to the Globally Optimal Vectorization of the Sorted Point Clouds
SN - 978-989-758-198-4
AU - Jelinek, A.
AU - Zalud, L.
PY - 2016
SP - 216
EP - 223
DO - 10.5220/0005962902160223

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.